scholarly journals Research on Fast Compensation Algorithm for Interframe Motion of Multimedia Video Based on Manhattan Distance

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Ning Li ◽  
Shuai Wan
Keyword(s):  
Signal To Noise Ratio ◽  
Manhattan Distance ◽  
Bit Rate ◽  
Signal To Noise ◽  
Search Range ◽  
Significant Information ◽  
Current Frame ◽  
Visual Effect ◽  
Compensation Algorithm ◽  
Noise Ratio

To improve the video quality, aiming at the problems of low peak signal-to-noise ratio, poor visual effect, and low bit rate of traditional methods, this paper proposes a fast compensation algorithm for the interframe motion of multimedia video based on Manhattan distance. The absolute median difference based on wavelet transform is used to estimate the multimedia video noise. According to the Gaussian noise variance estimation result, the active noise mixing forensics algorithm is used to preprocess the original video for noise mixing, and the fuzzy C-means clustering method is used to smoothly process the noisy multimedia video and obtain significant information from the multimedia video. The block-based motion idea is to divide each frame of the video sequence into nonoverlapping macroblocks, find the best position of the block corresponding to the current frame in the reference frame according to the specific search range and specific rules, and obtain the relative Manhattan distance between the current frame and the background of multimedia video using the Manhattan distance calculation formula. Then, the motion between the multimedia video frames is compensated. The experimental results show that the algorithm in this paper has a high peak signal-to-noise ratio and a high bit rate, which effectively improves the visual effect of the video.

scholarly journals Radio Polarimetry of Tycho's SNR

1990 ◽  
Vol 140 ◽  
pp. 76-78
Author(s):  
John R. Dickel ◽  
Wil J. M. Van Breugel ◽  
Richard G. Strom
Keyword(s):  
Faraday Rotation ◽  
Signal To Noise Ratio ◽  
Position Angle ◽  
Signal To Noise ◽  
Significant Information ◽  
Polarized Emission ◽  
Noise Ratio ◽  
Few Data ◽  
Faraday Effects ◽  
Tycho’S Snr

The remnant of Tycho's supernova of 1572 has been polarimetrically imaged using the 4 configurations of the VLA at wavelengths of 22 and 6 cm. A few data were also obtained at wavelengths of 21, 19, and 18 cm in the B configuration to check for any ambiguities in the Faraday rotation measurements and to look for deviations from the λ2 dependence of the Faraday rotation which would indicate significant internal Faraday effects. Although the total intensity shows structure on a scale of about 1 arcsecond the polarized emission appears to be resolved into cells of perhaps 10-arcsec size (1 arcsec corresponds to 0.011 pc at the 2.2 kpc distance to Tycho's SNR). We have therefore convolved the map shown in Figure 1 to a resolution of 4 arcsec to improve the signal-to-noise ratio. The contours represent the total intensity at 6-cm wavelength and the vectors show the position angle of the magnetic field with a length corresponding to the polarized intensity at 6 cm. In order to be seen, the vectors have a separation of 6 arcsec but no significant information is lost on this spacing.

Automatic modulation format/bit-rate classification and signal-to-noise ratio estimation using asynchronous delay-tap sampling

2015 ◽  
Vol 47 ◽  
pp. 126-133 ◽  
Author(s):  
Faisal Nadeem Khan ◽  
Chiew Hoon Teow ◽  
Shiu Guong Kiu ◽  
Ming Chieng Tan ◽  
Yudi Zhou ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Ratio Estimation ◽  
Bit Rate ◽  
Signal To Noise ◽  
Modulation Format ◽  
Noise Ratio

A New Image De-Noising Algorithm Based on Wavelet Transform

2012 ◽  
Vol 182-183 ◽  
pp. 1816-1820 ◽  
Author(s):  
Zhi Qiang Wang ◽  
Hui Shu An ◽  
Kai Cai Zhao ◽  
Yan Liang
Keyword(s):  
Wavelet Transform ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Similarity Function ◽  
Wavelet Coefficients ◽  
Signal To Noise ◽  
Edge Information ◽  
Visual Effect ◽  
Noise Ratio

This paper proposed a new image de-noising algorithm based on wavelet transform. Firstly, the algorithm made wavelet transform on the image, and then using the GGD described the wavelet coefficients of each sub band. Calculate the similarity of direction of horizontal, vertical and diagonal. Then adjust the coefficients according to similarity function. The experiment results showed that the algorithm not only remove the noise from the image but can protect the edge information of the image. The processing result had better visual effect and high signal to noise ratio.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

Quantifying the Effects of Background Speech Babble on Preschool Children's Novel Word Learning in a Multisession Paradigm: A Preliminary Study

2020 ◽  
Vol 63 (1) ◽  
pp. 345-356
Author(s):  
Meital Avivi-Reich ◽  
Megan Y. Roberts ◽  
Tina M. Grieco-Calub
Keyword(s):  
Word Learning ◽  
Signal To Noise Ratio ◽  
Preschool Age ◽  
Exposure Condition ◽  
Signal To Noise ◽  
Verbal Recall ◽  
Referent Selection ◽  
Main Effect ◽  
Noise Ratio ◽  
Novel Word Learning

Purpose This study tested the effects of background speech babble on novel word learning in preschool children with a multisession paradigm. Method Eight 3-year-old children were exposed to a total of 8 novel word–object pairs across 2 story books presented digitally. Each story contained 4 novel consonant–vowel–consonant nonwords. Children were exposed to both stories, one in quiet and one in the presence of 4-talker babble presented at 0-dB signal-to-noise ratio. After each story, children's learning was tested with a referent selection task and a verbal recall (naming) task. Children were exposed to and tested on the novel word–object pairs on 5 separate days within a 2-week span. Results A significant main effect of session was found for both referent selection and verbal recall. There was also a significant main effect of exposure condition on referent selection performance, with more referents correctly selected for word–object pairs that were presented in quiet compared to pairs presented in speech babble. Finally, children's verbal recall of novel words was statistically better than baseline performance (i.e., 0%) on Sessions 3–5 for words exposed in quiet, but only on Session 5 for words exposed in speech babble. Conclusions These findings suggest that background speech babble at 0-dB signal-to-noise ratio disrupts novel word learning in preschool-age children. As a result, children may need more time and more exposures of a novel word before they can recognize or verbally recall it.

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